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Audio Transcription MCP

An MCP server for local audio and video transcription with local Whisper or the OpenAI transcription API.

Package and CLI name: audio-transcription-mcp.

Requirements

  • Python 3.11+

  • ffmpeg available on PATH

  • For local transcription: install the local extra of cykk-audio-transcriber

  • For OpenAI transcription: install the api extra and set OPENAI_API_KEY

Install ffmpeg separately if it is not already available on your PATH. On Debian/Ubuntu, use sudo apt install ffmpeg; on macOS with Homebrew, use brew install ffmpeg; on Windows, install an FFmpeg build and add its bin directory to PATH.

Related MCP server: jackai-stt-mcp

Install from source

git clone https://github.com/cykk/audio-transcription-mcp.git
cd audio-transcription-mcp
pip install ".[local]"

To use the OpenAI transcription API instead:

pip install ".[api]"

Install from PyPI

After the package is published to PyPI, install it directly:

pip install "audio-transcription-mcp[local]"

For the OpenAI transcription API:

pip install "audio-transcription-mcp[api]"

Run

audio-transcription-mcp

For backward compatibility, audiototext-mcp remains available as an alias.

The server uses MCP stdio transport. Configure the command in an MCP client such as Claude Desktop, Cursor, or another compatible host:

{
  "mcpServers": {
    "audio-transcription": {
      "command": "audio-transcription-mcp"
    }
  }
}

Tool

transcribe_file accepts a local file_path and optional model, language, task, prompt, and api_key arguments. It returns JSON containing the detected language, full text, and timestamped segments.

The server reads local files, so only configure it in clients you trust. API keys should preferably be supplied through OPENAI_API_KEY rather than tool arguments.

Verify

After adding the server to an MCP client, call transcribe_file with a readable local audio or video file path. A successful response contains the detected language, full transcript, and timestamped segments.

To verify the package before configuring an MCP client, run:

python -c "import asyncio; from audiototext_mcp.server import mcp; print([tool.name for tool in asyncio.run(mcp.list_tools())])"

The command should include transcribe_file. A real transcription also requires an installed local Whisper extra or a valid OPENAI_API_KEY for the API extra.

License

MIT

Available Tools

1 tool
transcribe_fileA

Transcribe a local audio or video file and return JSON with text and timestamps.

Uses local Whisper by default. Set api_key (or OPENAI_API_KEY) to use the OpenAI speech API instead. The file must be readable by the MCP server.

Inputs: file_path (required), task, model, prompt, +2 more. Returns: result

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A4.1/5.0

    Scored across 1 tool

    Disambiguation5/5

    With only one tool, there is no possibility of confusion. The tool's purpose is clear and distinct by default.

    Naming Consistency5/5

    The single tool name 'transcribe_file' follows a clear verb_noun convention. With only one tool, there is no naming inconsistency to evaluate.

    Tool Count4/5

    A single tool is slightly below the typical 3-15 range, but it is well-scoped for a dedicated audio-to-text server. The tool fully addresses the server's narrow purpose without unnecessary additions.

    Completeness5/5

    The tool covers the complete transcription workflow: accepts local audio or video files, returns transcript with timestamps, and supports both local Whisper and OpenAI API backends. There are no obvious missing operations for this domain.

    Maintenance

    ActivityMaintained
    ResponsivenessNo recent community issues

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